Accelerating
Data Labeling:
A Comprehensive Review of Automated Techniques
A 23-page white paper designed to enhance the efficiency and accuracy of your automation processes.
In the machine learning pipeline, data labeling and quality assurance take up your time and resources. Automating these processes is vital to streamline your workflows and improve ROI.
This white paper explains automated labeling and suggests ways your team can enhance automation efficiency and accuracy.
Download to uncover:
- Key decision points when creating your automation strategy, with a spotlight on the four layers of automated labeling.
- Popular computer vision model building, annotation acceleration, and automated labeling approaches, including self-supervised and active learning.
- Effective automation strategies to enhance model performance, reduce annotation efforts, handle limited labeled data scenarios, and improve the efficiency of Vision AI model development.
- How CloudFactory applies Vision AI with cutting-edge approaches.
Learn from CloudFactory's experience as a leader in integrating people and technology to support the AI development lifecycle. We've implemented most annotation techniques covered in the white paper to help 700+ companies accelerate Vision AI model development.
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